We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Modelling shallow landslide susceptibility: a new approach in logistic regression by using favourability assessment.
- Authors
Domínguez-Cuesta, María José; Jiménez-Sánchez, Montserrat; Colubi, Ana; González-Rodríguez, Gil
- Abstract
A new method for estimating shallow landslide susceptibility by combining Geographical Information System (GIS), nonparametric kernel density estimation and logistic regression is described. Specifically, a logistic regression is applied to predict the spatial distribution by estimating the probability of occurrence of a landslide in a 16 km2 area. For this purpose, a GIS is employed to gather the relevant sample information connected with the landslides. The advantages of pre-processing the explanatory variables by nonparametric density estimation (for continuous variables) and a reclassification (for categorical/discrete ones) are discussed. The pre-processing leads to new explanatory variables, namely, some functions which measure the favourability of occurrence of a landslide. The resulting model correctly classifies 98.55% of the inventaried landslides and 89.80% of the landscape surface without instabilities. New data about recent shallow landslides were collected in order to validate the model, and 92.20% of them are also correctly classified. The results support the methodology and the extrapolation of the model to the whole study area (278 km2) in order to obtain susceptibility maps.
- Subjects
LANDSLIDES; GEOGRAPHIC information systems; NONPARAMETRIC signal detection; NUMERICAL analysis; PROBABILITY theory; METHODOLOGY; CASE studies; MAPS; GEOGRAPHY
- Publication
International Journal of Earth Sciences, 2010, Vol 99, Issue 3, p661
- ISSN
1437-3254
- Publication type
Article
- DOI
10.1007/s00531-008-0414-0